中性通量与信号显著性优化对半排他 $pp \to t\bar{t}$ 产生在深度学习训练中的影响
Impact of neutral fluxes and signal significance optimization on semi-exclusive $pp \to t\bar{t}$ production via deep learning training
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中文总结 AI 辅助
本研究通过蒙特卡洛模拟和TensorFlow深度学习，评估了中性通量对半排他t-tbar产生的影响，并优化信号显著性，在LHC和FCC能量下实现AUC 0.9917，预测5σ显著性，为实验观测提供潜力。
中文摘要 AI 辅助
在蒙特卡洛模拟中实现了光子通量基准模型以及最近对pomeron能量通量和结构函数的实验估计，以评估它们对尚未观测到的半排他 $t\bar{t}$ 产生在大型强子对撞机（LHC）和未来环形对撞机（FCC）能量下的质子-质子（$pp$）碰撞中的物理可观测量和信号强度不确定性的影响。从LHC到FCC能量，预期的截面分别增加约50倍和22倍，分别对应pomeron诱导和光子诱导过程。TensorFlow深度神经网络将半排他过程与非边缘 $t\bar{t}X$ 背景区分开来，对于光子诱导信号，测试接收者操作特征曲线下面积（AUC）达到 $0.9917 \pm 0.0002$。在探测器层面，使用CERN的CMS探测器几何结构，最小Hadronic Forward能量可观测量被确定为对抗该背景的最有效判别器。对于低堆积 $pp$ 数据，一个包含统计不确定性和来自pomeron与光子方案的系统贡献的Asimov数据集分析预测，对于pomeron诱导和光子诱导的 $t\bar{t}$ 产生，在积分亮度分别为1和4.7 $\mathrm{fb}^{-1}$ 时，显著性达到 $5σ$。系统贡献占总不确定性的比例分别为25.1%和7.6%。这些结果突显了使用LHC Run 2和Run 3数据以及LHC前向物理计划内进一步研究的实验观测潜力。
英文摘要
Photon flux benchmark models and recent experimental estimates of pomeron energy fluxes and structure functions are implemented in Monte Carlo simulations to assess their impact on physical observables and signal strength uncertainty for the yet-to-be-observed semi-exclusive $t\bar{t}$ production in proton-proton ($pp$) collisions at Large Hadron Collider (LHC) and Future Circular Collider (FCC) energies. The expected cross sections increase by factors of approximately 50 and 22 for pomeron-induced and photon-induced processes, respectively, from LHC to FCC energies. TensorFlow deep neural networks discriminate semi-exclusive processes from the non-peripheral $t\bar{t}X$ background, achieving a test area under the receiver operating characteristic curve (AUC) of $0.9917 \pm 0.0002$ for the photon-induced signal. At detector level, using the CMS detector geometry at CERN, the minimum Hadronic Forward energy observable is identified as the most effective discriminator against this background. For low-pileup $pp$ data, an Asimov dataset analysis incorporating statistical uncertainties and systematic contributions from pomeron and photon schemes predicts a significance of $5σ$ for pomeron-induced and photon-induced $t\bar{t}$ production with integrated luminosities of 1 and 4.7 $\mathrm{fb}^{-1}$, respectively. The systematic contributions to the total uncertainty are 25.1% and 7.6%, respectively. These results highlight the potential for experimental observation using Run 2 and Run 3 LHC data and for further studies within the LHC forward physics program.
发表机构
- Universidad de Sonora（索诺拉大学）
- The University of Kansas（堪萨斯大学）
机构由 AI 辅助整理，请以论文原文为准。
